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A quadratic time dynamic programming algorithm can be used to compute an approximate solution to the problem of finding the most likely changepoints with respect to the Poisson likelihood, subject to a constraint on the number of segments, and the changes which must alternate: up, down, up, down, etc. For more info read <http://proceedings.mlr.press/v37/hocking15.html> "PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count data" by TD Hocking et al, proceedings of ICML2015.
| Version: | 2024.1.24 |
| Depends: | R (≥ 2.10) |
| Suggests: | ggplot2 (≥ 2.0), testthat, penaltyLearning |
| Published: | 2024-01-24 |
| Author: | Toby Dylan Hocking, Guillem Rigaill |
| Maintainer: | Toby Dylan Hocking <toby.hocking at r-project.org> |
| BugReports: | https://github.com/tdhock/PeakSegDP/issues |
| License: | GPL-3 |
| URL: | https://github.com/tdhock/PeakSegDP |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | PeakSegDP results |
| Reference manual: | PeakSegDP.pdf |
| Package source: | PeakSegDP_2024.1.24.tar.gz |
| Windows binaries: | r-devel: PeakSegDP_2024.1.24.zip, r-release: PeakSegDP_2024.1.24.zip, r-oldrel: PeakSegDP_2024.1.24.zip |
| macOS binaries: | r-release (arm64): PeakSegDP_2024.1.24.tgz, r-oldrel (arm64): PeakSegDP_2024.1.24.tgz, r-release (x86_64): PeakSegDP_2024.1.24.tgz, r-oldrel (x86_64): PeakSegDP_2024.1.24.tgz |
| Old sources: | PeakSegDP archive |
| Reverse suggests: | PeakSegOptimal |
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