PeakSegOptimal
2024.10.1Optimal Segmentation Subject to Up-Down Constraints
Overview
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.
Install
Health
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
Documentation signals are not tracked yet for this package.
Downloads
Repository
Repository practices
1 development-tooling and community-health practice detected across 1 family in the upstream repository
Checks run against github.com/tdhock/peaksegoptimal on 2026-07-19.
Dependencies
Nothing depends on this yet.
Code & Tests
Datasets
People & History
6 releases. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 2024.10.1Latest
- RR 4.4.0 released · 2024-04-24
- 2024.1.242024-01-24 · diff ↗
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- 2018.05.252018-05-25 · diff ↗
- RR 3.5.0 released · 2018-04-23
- 2017.07.122017-07-12 · diff ↗
- 2017.07.112017-07-11 · diff ↗
- 2017.06.202017-06-21
- RR 3.4.0 released · 2017-04-21
Package metadata
- First published
- 2017-06-21
- Total releases
- 6 / 9 yrs
- License
- GPL-3 OSI
- Download size
- 127 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet