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Bibliographic Details
Main Authors: Danese, Luca, Corradin, Riccardo, Ongaro, Andrea
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2511.04785
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author Danese, Luca
Corradin, Riccardo
Ongaro, Andrea
author_facet Danese, Luca
Corradin, Riccardo
Ongaro, Andrea
contents We introduce BayesChange, a computationally efficient R package, built on C++, for Bayesian change point detection and clustering of observations sharing common change points. While many R packages exist for change point analysis, BayesChange offers methods not currently available elsewhere. The core functions are implemented in C++ to ensures computational efficiency, while an R user interface simplifies the package usage. The BayesChange package includes two R wrappers that integrate the C++ backend functions, along with S3 methods for summarizing the results. We present the theory beyond each method, the algorithms for posterior simulation and we illustrate the package's usage through synthetic examples.
format Preprint
id arxiv_https___arxiv_org_abs_2511_04785
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle BayesChange: an R package for Bayesian Change Point Analysis
Danese, Luca
Corradin, Riccardo
Ongaro, Andrea
Computation
We introduce BayesChange, a computationally efficient R package, built on C++, for Bayesian change point detection and clustering of observations sharing common change points. While many R packages exist for change point analysis, BayesChange offers methods not currently available elsewhere. The core functions are implemented in C++ to ensures computational efficiency, while an R user interface simplifies the package usage. The BayesChange package includes two R wrappers that integrate the C++ backend functions, along with S3 methods for summarizing the results. We present the theory beyond each method, the algorithms for posterior simulation and we illustrate the package's usage through synthetic examples.
title BayesChange: an R package for Bayesian Change Point Analysis
topic Computation
url https://arxiv.org/abs/2511.04785