BayesChange: Bayesian Methods for Change Points Analysis
Perform change points detection on univariate and multivariate time series according to the methods presented by Asael Fabian Martínez and Ramsés H. Mena (2014) <doi:10.1214/14-BA878> and Corradin, Danese and Ongaro (2022) <doi:10.1016/j.ijar.2021.12.019>. It also clusters different types of time dependent data with common change points, see "Model-based clustering of time-dependent observations with common structural changes" (Corradin,Danese,KhudaBukhsh and Ongaro, 2024) <doi:10.48550/arXiv.2410.09552> for details.
| Version: | 2.1.3 |
| Depends: | R (≥ 3.5.0) |
| Imports: | Rcpp,salso,dplyr,tidyr,ggplot2,ggpubr |
| LinkingTo: | Rcpp,RcppArmadillo,RcppGSL |
| Suggests: | knitr,rmarkdown,testthat (≥ 3.0.0) |
| Published: | 2025-11-11 |
| DOI: | 10.32614/CRAN.package.BayesChange |
| Author: | Luca Danese [aut, cre, cph], Riccardo Corradin [aut], Andrea Ongaro [aut] |
| Maintainer: | Luca Danese <l.danese1 at campus.unimib.it> |
| BugReports: | https://github.com/lucadanese/BayesChange/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/lucadanese/BayesChange |
| NeedsCompilation: | yes |
| Materials: | README,NEWS |
| In views: | TimeSeries |
| CRAN checks: | BayesChange results |
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