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RegimeChange

Comprehensive Regime Change Detection in Time Series

v0.1.1 · Feb 13, 2026 · MIT + file LICENSE

Description

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.

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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Dependency Network

Dependencies Reverse dependencies ggplot2 rlang cli magrittr RegimeChange

Version History

new 0.1.1 Mar 9, 2026