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 "Constrained Dynamic Programming and Supervised Penalty Learning Algorithms for Peak Detection" <https://jmlr.org/papers/v21/18-843.html> by TD Hocking et al.
Version: | 2024.10.1 |
Depends: | R (≥ 2.10) |
Imports: | penaltyLearning |
Suggests: | PeakSegDP (≥ 2016.08.06), ggplot2, testthat, data.table (≥ 1.9.8) |
Published: | 2024-10-02 |
DOI: | 10.32614/CRAN.package.PeakSegOptimal |
Author: | Toby Dylan Hocking [aut, cre] |
Maintainer: | Toby Dylan Hocking <toby.hocking at r-project.org> |
BugReports: | https://github.com/tdhock/PeakSegOptimal/issues |
License: | GPL-3 |
URL: | https://github.com/tdhock/PeakSegOptimal |
NeedsCompilation: | yes |
Materials: | NEWS |
In views: | Omics |
CRAN checks: | PeakSegOptimal results |
Reference manual: | PeakSegOptimal.pdf |
Package source: | PeakSegOptimal_2024.10.1.tar.gz |
Windows binaries: | r-devel: PeakSegOptimal_2024.10.1.zip, r-release: PeakSegOptimal_2024.10.1.zip, r-oldrel: PeakSegOptimal_2024.10.1.zip |
macOS binaries: | r-release (arm64): PeakSegOptimal_2024.10.1.tgz, r-oldrel (arm64): PeakSegOptimal_2024.10.1.tgz, r-release (x86_64): PeakSegOptimal_2024.10.1.tgz, r-oldrel (x86_64): PeakSegOptimal_2024.10.1.tgz |
Old sources: | PeakSegOptimal archive |
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