PeakSegOptimal: Optimal Segmentation Subject to Up-Down Constraints

Computes optimal changepoint models using the Poisson likelihood for non-negative count data, subject to the PeakSeg constraint: the first change must be up, second change down, third change up, etc. For more info about the models and algorithms, read "A log-linear time algorithm for constrained changepoint detection" <arXiv:1703.03352> by TD Hocking et al.

Version: 2017.07.12
Depends: R (≥ 2.10)
Imports: penaltyLearning
Suggests: PeakSegDP (≥ 2016.08.06), ggplot2, testthat, data.table (≥ 1.9.8)
Published: 2017-07-12
Author: Toby Dylan Hocking
Maintainer: Toby Dylan Hocking <toby.hocking at r-project.org>
License: GPL-3
NeedsCompilation: yes
Materials: NEWS
CRAN checks: PeakSegOptimal results

Downloads:

Reference manual: PeakSegOptimal.pdf
Package source: PeakSegOptimal_2017.07.12.tar.gz
Windows binaries: r-devel: PeakSegOptimal_2017.07.12.zip, r-release: PeakSegOptimal_2017.07.12.zip, r-oldrel: PeakSegOptimal_2017.07.12.zip
OS X binaries: r-release: PeakSegOptimal_2017.07.12.tgz, r-oldrel: PeakSegOptimal_2017.07.12.tgz
Old sources: PeakSegOptimal archive

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