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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 "Constrained Dynamic Programming and Supervised Penalty Learning Algorithms for Peak Detection" <https://jmlr.org/papers/v21/18-843.html> by TD Hocking et al.
Getting started
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Package details |
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| Author | Toby Dylan Hocking [aut, cre] |
| Maintainer | Toby Dylan Hocking <toby.hocking@r-project.org> |
| License | GPL-3 |
| Version | 2024.10.1 |
| URL | https://github.com/tdhock/PeakSegOptimal |
| Package repository | View on CRAN |
| Installation |
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