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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.
Package details |
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Author | Toby Dylan Hocking, Guillem Rigaill |
Maintainer | Toby Dylan Hocking <toby.hocking@r-project.org> |
License | GPL-3 |
Version | 2024.1.24 |
URL | https://github.com/tdhock/PeakSegDP |
Package repository | View on CRAN |
Installation |
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