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RegimeChange  

Comprehensive Regime Change Detection in Time Series
View on CRAN: Click here


Download and install RegimeChange package within the R console
Install from CRAN:
install.packages("RegimeChange")

Install from Github:
library("remotes")
install_github("cran/RegimeChange")

Install by package version:
library("remotes")
install_version("RegimeChange", "0.1.1")



Attach the package and use:
library("RegimeChange")
Maintained by
José Mauricio Gómez Julián
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-02-13
Latest Update: 2026-02-13
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.
How to cite:
José Mauricio Gómez Julián (2026). RegimeChange: Comprehensive Regime Change Detection in Time Series. R package version 0.1.1, https://cran.r-project.org/web/packages/RegimeChange. Accessed 13 Sep. 2026.
Previous versions and publish date:
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Functions, R codes and Examples using the RegimeChange R package
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