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: |
2.0.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
Rcpp, salso, dplyr, tidyr, ggplot2, ggpubr |
| LinkingTo: |
Rcpp, RcppArmadillo, RcppGSL |
| Suggests: |
knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2025-03-12 |
| 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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