Perform change points detection on univariate and multivariate time series according to the methods presented by Asael Fabian MartÃnez 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: 2.1.0 Depends: R (≥ 3.5.0) Imports: Rcpp, salso, dplyr, tidyr, ggplot2, ggpubr LinkingTo: Rcpp, RcppArmadillo, RcppGSL Suggests: knitr, rmarkdown, testthat (≥ 3.0.0) Published: 2025-04-28 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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=BayesChange to link to this page.
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