Package: BayesChange 1.1.1

Luca Danese
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.
Authors:
BayesChange_1.1.1.tar.gz
BayesChange_1.1.1.tar.gz(r-4.5-noble)BayesChange_1.1.1.tar.gz(r-4.4-noble)
BayesChange_1.1.1.tgz(r-4.4-emscripten)BayesChange_1.1.1.tgz(r-4.3-emscripten)
BayesChange.pdf |BayesChange.html✨
BayesChange/json (API)
NEWS
# Install 'BayesChange' in R: |
install.packages('BayesChange', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/lucadanese/bayeschange/issues
Last updated 6 days agofrom:7df4a06067. Checks:2 OK. Indexed: no.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Feb 15 2025 |
R-4.5-linux-x86_64 | OK | Feb 15 2025 |
Exports:clust_cp_epiclust_cp_multiclust_cp_unidetect_cp_multidetect_cp_uniget_clust_VIsim_epi_data
Dependencies:RcppRcppArmadilloRcppGSL
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Clustering Epidemiological survival functions with common changes in time | clust_cp_epi |
Clustering multivariate times series with common changes in time | clust_cp_multi |
Clustering univariate times series with common changes in time | clust_cp_uni |
Detect Change Points on multivariate time series | detect_cp_multi |
Detect Change Points on an univariate time series. | detect_cp_uni |
Estimate order | get_clust_VI |
Compute the posterior similarity matrix | psm |
Simulate epidemiological data | sim_epi_data |