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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 |
DOI: | 10.32614/CRAN.package.PeakSegDP |
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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