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: | 2018.05.25 |
| Depends: | R (≥ 2.10) |
| Imports: | penaltyLearning |
| Suggests: | PeakSegDP (≥ 2016.08.06), ggplot2, testthat, data.table (≥ 1.9.8) |
| Published: | 2018-05-25 |
| 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 |
| Reference manual: | PeakSegOptimal.pdf |
| Package source: | PeakSegOptimal_2018.05.25.tar.gz |
| Windows binaries: | r-devel: PeakSegOptimal_2018.05.25.zip, r-release: PeakSegOptimal_2018.05.25.zip, r-oldrel: PeakSegOptimal_2018.05.25.zip |
| macOS binaries: | r-release (arm64): PeakSegOptimal_2018.05.25.tgz, r-oldrel (arm64): PeakSegOptimal_2018.05.25.tgz, r-release (x86_64): PeakSegOptimal_2018.05.25.tgz, r-oldrel (x86_64): PeakSegOptimal_2018.05.25.tgz |
| Old sources: | PeakSegOptimal archive |
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