Comprehensive Regime Change Detection in Time Series R package RegimeChange version 0.1.1 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. Software Depends: R (>= 4.0.0) Imports: stats, ggplot2 (>= 3.4.0), rlang (>= 1.1.0), cli (>= 3.6.0), magrittr Suggests: testthat (>= 3.0.0), knitr, rmarkdown, plotly, patchwork, covr, JuliaCall (>= 0.17.0), keras (>= 2.9.0), tensorflow (>= 2.9.0), reticulate (>= 1.26) José Mauricio Gómez Julián <isadorenabi@pm.me> Comprehensive R Archive Network (CRAN) José Mauricio Gómez Julián [aut, cre] (ORCID: <https://orcid.org/0009-0000-2412-3150>) MIT + file LICENSE (https://CRAN.R-project.org/package=RegimeChange/LICENSE) 2026-02-13 application/tgz https://CRAN.R-project.org/package=RegimeChange doi:10.32614/CRAN.package.RegimeChange