RegimeChange
0.1.1Comprehensive Regime Change Detection in Time Series
Overview
A unified framework for detecting regime changes (changepoints) in time series data. Implements both frequentist methods including Cumulative Sum (CUSUM, Page (1954) doi:10.1093/biomet/41.1-2.100), Pruned Exact Linear Time (PELT, Killick, Fearnhead, and Eckley (2012) doi:10.1080/01621459.2012.737745), Binary Segmentation, and Wild Binary Segmentation, as well as Bayesian methods such as Bayesian Online Changepoint Detection (BOCPD, Adams and MacKay (2007) doi:10.48550/arXiv.0710.3742 and Shiryaev-Roberts. Supports offline analysis for retrospective detection and online monitoring for real-time surveillance. Provides rigorous uncertainty quantification through confidence intervals and posterior distributions. Handles univariate and multivariate series with detection of changes in mean, variance, trend, and distributional properties.
Install
Health
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 73%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 24%
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Checks run against github.com/isadorenabi/regimechange on 2026-07-26.
Dependencies
Code & Tests
Datasets
People & History
1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.1.1Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2026-02-13
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 4.0.0
- Bundled data
- 33 KB / 4 files
- Download size
- 193 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet